1. Field of the Invention
The present invention relates to a data processing system consisting of a neural network for configuration of voice recognition from data or voice.
2. Description of the Related Art
The neural network in this kind of data processing system consists of layers including neuron model (neuron, hereinafter) 1 in parallel, as shown in FIG. 3. In neuron 1, data DI1, DI2, DT3, . . . DIn to be inputted to neuron 1 from the outside are multiplied by weights W1, W2, W3, . . . , Wn, respectively. Data D0 is outputted corresponding to the comparison result between the sum of them and threshold ".theta.". There are various manners to compare them. One of them, for example, is settled that the output data D0 becomes "1" when the sum is equal or more than the threshold ".theta." and the output data D0 becomes "0" when it is less then the threshold ".theta.".
A neural layer is constructed by arranging multiple neurons such as that shown in FIG. 4 in parallel. An input data for an image processing system comprising such neural layers is inputted to the first neural layer. The input data is a pixel data of a configuration.
It is difficult for such an image processing system to realize a practical system because numerous neurons are necessary to execute necessary recognition processing from all pixel data. It is separative theory from organism processing that pixel data itself is inputted to neural network.
Therefore, there has never been clarified the relationship between the data processing to be performed in a neural network and the capacity or construction of neural network. Accordingly, it has been unknown if constructed neural network achieve the expected performance until an experiment result is obtained.
DP matching method the most practical method for acoustic recognition, a successful result is reported of recognition ratio of 85%.
In DP matching, characteristics of frequency and power are extracted, then a pattern matching is performed between reference phonetic pattern and inputted data, for recognition. (Processes referred to here as "characteristic extraction" are also referred to as "feature extraction.") The rule for the pattern matching must be determined according to a plurality of sampling data. It causes a limitation of recognition facility.
The present invention is invented so as to solve the above problems and has an object to provide an image recognition system possible to process various kinds of characteristic variable in high recognition ratio.